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The Name of the Game in PHM Is Variability: Part 4 - Targeting

by Scott MacStravic

The first purpose of the assessment process is to determine the size of the PHM challenge and of potential gains from implementing a PHM strategy.  The assessment process is then also used in the evaluation process, to identify changes in measured “success” dimensions against the baseline data.  But another key use of the data is to identify and select which members of the population make the most promising targets for participation in which PHM intervention, together with how many available interventions will likely justify their investment.

This step begins with identifying the baseline costs, both direct and indirect when applied to employee populations, linked to individuals and the health-related factors each has been found to have.  Usually, without extensive multivariate analysis and predictive modeling, the “potential” is estimated based solely on the baseline costs.  But the real predictor of potential economic gains lies in the particular PHM interventions that will be applied on a DIY or outsourced basis.  And this information is peculiar to each PHM strategy, intervention, and supplier, rather than any generalizable average for PHM as a whole.

Moreover, when measurement problems such as side-by-side comparison “self-selection bias” and before/after “regression to the mean” effects have been overcome, there remains the inherent difficulty of predicting realistic potential cost impacts or other benefits based on past data.  While past data may accurately describe the past of the very population to be addressed by PHM, it does not translate easily into predictions of the future.  And while a given PHM supplier’s own past performance may be “statistically valid and reliable”, it may not be a sound basis for accurate prediction of results in a new population.

Within these limits, PHM investors and suppliers will want to determine which and how many population members represent the best risk/reward potential for which particular PHM interventions.  Some suppliers and employers have employed a completely customized approach to PHM, where each individual either chooses each’s own goals or is assigned a coach who will customize the intervention to the individual’s mix of challenges, and address as many of each’s individual problems as possible.  Experience suggests that individuals can handle more than one, but rarely more than two or three, so the number of problems to be addressed is normally small.

In many cases, there is one specific problem that is the basis for the PHM intervention to which members of the population will be invited.  This does not mean that the intervention will have a very narrow focus, however, though it may.  A smoking cessation program normally focuses exclusively on enabling participants to quit, but may have to address a wide range of perceived barriers and related issues, including stress and weight management along with the smoking behavior, per se.  And diabetes disease management interventions routinely include attention to blood pressure and cholesterol levels, in addition to blood glucose.

While the baseline costs linked to individuals may guide targeting to some extent, the psychographic data indicating the probability that each will make a needed change and achieve success thereby, together with PHM suppliers’ demonstrated performance will add significantly to how “informed” the choice of targets can become.  In many cases, the supplier may guarantee results for particular population segments, interventions, or success dimensions, making the targeting that much better informed.

Targeting necessarily includes consideration of how PHM suppliers charge, and what additional costs may be incurred by targeting more and particular segments or individuals for interventions.  When the supplier charges on a “per population” of flat fee basis, it will not add fee costs to include as many members of the population in any given intervention, though most charge a fee for each separate intervention, which will multiply costs by the number of interventions selected, rather than the number of members participating.

When the supplier charges per participant, perhaps with graduated fees based on the risk/reward potential it determines for each and the different intensity/expense for the graduated interventions, it is the number of members targeted for each intervention that will represent the upper limit on fees.  Moreover, payers will likely incur additional costs, per member, per participant, or even per successful participant (e.g. when incentives are offered for success rather than participation alone), which have to be considered as well.  And while payers may recommend steps their clients should take that incur costs, the client will have the last word on which kinds of support it provides and what it will pay for what.

There will always be the unknown costs of participation or success incentives that will have to be paid, but this will typically be substantially less than the economic gains associated therewith.  The past performance of the supplier applied to the baseline costs and economic value of members of the actual population to be addressed should help in ensuring that the client’s total costs are kept lower than the client’s benefits. Controlling the number of members targeted and number of interventions invested in based on risk/reward vs. predicted or controllable costs, is the best overall approach to take.


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